Web portals pioneered as one of the earliest adopters of adaptation and personalization techniques to help users deal with the problem of information overload. Nowadays, a large number of organizations use them as a single-point of access to the vast amount of resources available on the Web and in enterprise intranets. Some organizations strive to make portals adaptive to users and to the context they work in, so that the users will be provided with the right information at the right time. There are different kinds of adaptation effects that users may encounter in an adaptive portal, e.g. the portal's front page displaying recently added resources containing information that the user is interested in, modifying navigation topology to promote interesting pages to better positions, augmenting portal content with additional information that matches the user's current interests, and so on. In order to achieve such adaptation effects, the following criteria may be met.
Firstly, the portal may have a user model containing information about various user features, such as interests, expertise, and traits as well as information about the various contexts that users work in and the rules governing what features have which importance in which context.
Secondly, portal resources may be semantically described so that the adaptation component may automatically select the resources that match user information needs in a given context.
Thirdly, the portal may have a domain knowledge model providing machine readable semantics of the information that is used for describing user features and portal resources.
E.g., patent application US 2009/0287989A1 describes a content manager configured to present a website and a user profile repository including user profile information indicating user interests and preferences. Another patent application, U.S. Pat. No. 6,539,375B2, describes a method for profiling a user of the Internet according to predefined categories of interest. The document discloses scanning content information of an Internet user to generate unknown data and processing unknown data to determine its relevance to predefined categories of interest.
In most adaptive portals, users may only see a final adaptation effect, e.g., a list of recommended items or a modified navigation topology. The mechanism of the adaptation process itself as well as the user model and the domain knowledge model are hidden from users. This harms the overall usability of the system and its acceptance by the users. As a consequence, negative user experiences with the respective portal may become reality. Some of the reasons are listed here:
Firstly, users do not understand how the adaptation works, e.g., why they get recommendations to certain resources.
Secondly, users have a very limited control over the adaptation, which may lead to errors and misunderstandings. For instance, if a user cannot view and modify his own user model, she or he cannot notice and correct wrong assumptions the system makes about her or his interests. This may result in receiving recommendations to irrelevant information.
Thus, there may be a need for an improved architecture for a method for an interactive visualization of a user interest model via an interactive graphical user interface such that the way a user may influence the information in the user interest model is modifiable.